In addition to the word-based and POS-based bigram and trigram models, class-based language models can be optionally used [46].
This paper shows how to combine ontological and model-based techniques in languages that facilitate collaborative design exploration.
In this paper we describe how to use AORTA with a formal data model, allowing integration with a variety of model-based data specification languages.
Tables 7 and 8 show the performance of various methods on the test and development data in Subtask 2. As can be seen, cosine similarity performs much better than Indri, a classical language model-based method, on exact performance but inferior on hierarchy performance.
The second part of this chapter will address these requirements and discuss a novel approach to engineering semantic models, which allows seamlessly supporting existing software engineering models in Unified Modeling Language or other modeling languages in semantic model-based enterprise application development.
This paper addresses this problem by presenting a programming model called PTIDES that serves as a coordination language for model-based design of distributed real-time embedded systems.
The papers discuss all aspects of object technology and related fields, in particular model-based development, component-based development, language implementation and patterns, in a holistic way.
In the first recognition pass, we typically make use of acoustic models and word-based language models.
The only exception is the P1B-HTK system, which employs a phone-based ASR subsystem, and hence both in-vocabulary and out-of-vocabulary terms are treated equally (since the training/development data are provided by the organizers, and thus the in-vocabulary terms have not been used for acoustic model and phone-based language model training).
Puppet is an open source configuration and management tool implemented in Ruby [47] that allows expressing in a custom declarative language using a model-based approach [73].
The five analytical techniques are cosine similarity using term frequency-inverse document frequency vectors (tf-idf cosine), latent semantic analysis (LSA), topic modeling, and two Poisson-based language models – BM25 and PMRA (PubMed Related Articles).
